BB839: Planning and evaluation of biological studies
Study Board of Science
Teaching language: English
EKA: N110015112, N110015102
Assessment: Second examiner: None, Second examiner: Internal
Grading: Pass/Fail, 7-point grading scale
Offered in: Odense
Offered in: Autumn
Level: Master's level course approved as PhD course
STADS ID (UVA): N110015101
ECTS value: 5
Date of Approval: 02-03-2020
Duration: 1 semester
Version: Archive
Comment
Entry requirements
Academic preconditions
Students taking the course are expected to:
- Have basic knowledge of statistics and mathematics
- Have a Bachelor’s degree in a field with some level or focus on quantitative methods
Course introduction
The aim of this course is to provide students with the tools to explore, analyse, and interpret data, and to present the results of biological studies.
The course builds on knowledge acquired in previous courses in mathematics and statistics.
The course gives an academic basis for work carried out in individual study activities and the masters project.
In relation to the competence profile of the degree it is the explicit focus of the course to:
- Develop skills in data exploration, visualisation and interpretation.
- Develop the students’ competence to undertake appropriate quantitative analysis of the student’s own data (e.g. masters project).
- Develop skills to critically evaluate statistical analyses (e.g. in scientific papers/presentations).
- Develop skills to use the R statistical software for analysis and graphing.
- Structure personal learning
Expected learning outcome
The learning objectives of the course are that the student demonstrates the ability to:
- formulate appropriate scientific questions in biological disciplines, e.g. ecology, physiology, neurobiology, and evolutionary biology.
- design appropriate laboratory or field studies in order to address scientific questions.
- manipulate and explore visually data from experimental and field studies.
- select appropriate statistical approaches for a variety of different data types.
- fit and interpret appropriate regression models (ordinary least squares, generalised linear models), randomisation tests, and “classical tests” (t-tests, chi-squared tests etc.).
- understand and commonly used model selection approaches.
- present quantitative the results from biological studies, including graphically.
Content
The following main topics are contained in the course:
- Questions and hypotheses in research
- Designing data collection for biological studies
- Manipulating data with R (dplyr, tidyr, magrittr)
- Visualising data with R (ggplot2)
- Regression models, randomisation tests and “classical” tests
- Model selection
- Presenting results of statistical analyses
Literature
Beckerman, Childs & Petchey (2017) Getting Started With R. 2nd Edition. Oxford University Press.
Other literature uploaded to, or linked to, on Blackboard.
See Blackboard for syllabus lists and additional literature references.
Examination regulations
Prerequisites for participating in the exam a)
Timing
Autumn
Tests
Mandatory assignments
EKA
N110015112
Assessment
Second examiner: None
Grading
Pass/Fail
Identification
Full name and SDU username
Language
Normally, the same as teaching language
Examination aids
To be announced during the course
ECTS value
0
Additional information
As a prerequisites for participating in the exam the student must hand in 80% of the non-graded problem sets.
The prerequisite examination is a prerequisite for participation in exam element a)
Exam element a)
Timing
Autumn
Prerequisites
| Type | Prerequisite name | Prerequisite course |
|---|---|---|
| Examination part | Prerequisites for participating in the exam a) | N110015101, BB839: Planning and evaluation of biological studies |
Tests
Written project
EKA
N110015102
Assessment
Second examiner: Internal
Grading
7-point grading scale
Identification
Student Identification Card
Language
Normally, the same as teaching language
Examination aids
To be announced during the course.
ECTS value
5
Additional information
Reexam in the same exam period or immediately thereafter.
The mode of exam at the re-examination may differ from the mode of exam at the ordinary exam.
The mode of exam at the re-examination may differ from the mode of exam at the ordinary exam.
Indicative number of lessons
Teaching Method
At the faculty of science, teaching is organized after the three-phase model ie. intro, training and study phase.
Activities during the study phase:
- Computer-based exercises
- Research oriented learning (guided exploration of data)
- Reading relevant literature, or other written material (e.g. blog posts)